Entering edit mode
Dear Paul,
Your description of the limma model you've fitted is very clear, but
you haven't explained exactly
what is in your picture. The data values on the y-axis don't appear
to be the M-values you used
to fit the linear model, because we don't see the up-down pattern we'd
expect to see from
dye-swaps. How have you obtained "fitted values"? Note that M-values
are already log-ratios, so
it doesn't make sense to write "log2M".
lmFit() simply does least squares regression. It gives the same
coefficients that you would get
from lm() for each gene. I suggest that you extract the M-value data
for one gene, and experiment
with fitting the data using lm(), until you're satisfied that you
understand the parametrization
and fitted values.
Best wishes
Gordon
> [BioC] limma question: direct two-color design & modeling individual
subject effects
> Paul Shannon pshannon at systemsbiology.org
> Mon Apr 30 05:08:15 CEST 2007
>
> I've been working on and off for a few months with limma on a set of
28 2-color
> arrays made up of 14 dye-swap pairs. The main contrast in the
arrays is between
> malaria parasite RNA extracted from maternal and from juvenile
hosts;
> all the arrays can be described in these terms. This is the main
effect we
> are studying, and limma is very helpful in elucidating it.
>
> The arrays can be more specifically described as comparisons between
specific
> maternal subjects and specific juvenile subjects -- between
different
> combinations of three mothers (m918, m836, m920) with six children
(c073, c135,
> c140, c372, c451, c413, c425). I have trouble fitting models to
some of these
> genes, failing to isolatethe effects of individual subjects where
their effects seem
> to be strong.
>
> (A good example can be seen at
http://gaggle.systemsbiology.net/pshannon/tmp/7346.png,
> where the effect of m920 is pronounced, but apparently missed by my
lmFit/eBayes model.)
>
> Here are some few lines from each of the matrices I use that lead to
that plot.
>
> ---- head (targets)
>
> SlideNumber Name FileName Cy3 Cy5 Mother
Child
> 1 2254 slide2254 m918c073-cy3cy5.gpr maternal juvenile m918
c073
> 2 2261 slide2261 m918c073-cy5cy3.gpr juvenile maternal m918
c073
> 3 2258 slide2258 m836c073-cy3cy5.gpr maternal juvenile m836
c073
> 4 2265 slide2265 m836c073-cy5cy3.gpr juvenile maternal m836
c073
> 5 2341 slide2341 m836c135-cy3cy5.gpr maternal juvenile m836
c135
> 6 2344 slide2344 m836c135-cy5cy3.gpr juvenile maternal m836
c135
>
> ----- head (design)
>
> mother child maternal
> 1 m918 c073 Low
> 2 m918 c073 High
> 3 m836 c073 Low
> 4 m836 c073 High
> 5 m836 c135 Low
> 6 m836 c135 High
>
> ---- create the model
>
> model <- model.matrix (~maternal + mother + child, design)
>
> head (model)
> (Intercept) maternalHigh motherm918 motherm920 childc135 childc140
childc372 childc413
childc425 childc451
> 1 1 0 1 0 0 0
0 0
0 0
> 2 1 1 1 0 0 0
0 0
0 0
> 3 1 0 0 0 0 0
0 0
0 0
> 4 1 1 0 0 0 0
0 0
0 0
> 5 1 0 0 0 1 0
0 0
0 0
> 6 1 1 0 0 1 0
0 0
0 0
>
> ---- fit the data
>
> fit <- lmFit (MA, model)
> efit <- eBayes (fit)
>
> # one example of poor fit. with probe 7346, the m920 effect is very
strong, but the coefficients
> # don't reflect that. instead, most of the influence is allocated
to the maternal effect, which
> # nicely models all the comparisons except those involving m920.
the fit there is strikingly
> # poor, with high residuals. I can't make sense of the tiny
motherm920 coefficient:
>
> > efit$coef [7346,]
> (Intercept) maternalHigh motherm918 motherm920 childc135
childc140 childc372
childc413 childc425 childc451
> -3.62867124 7.49268173 0.24858455 -0.02635289 -0.67898282
-0.24566235 -0.24673763
0.10618603 -0.37520911 -0.02761610
>
> The plot of the fitted & actual values can be found at
>
> http://gaggle.systemsbiology.net/pshannon/tmp/7346.png
>
> I may be over-interpreting, or mis-interpreting, or even
misrepresenting all this. But after lots
> of head scratching, lots of reading and experiments, I can't get the
coefficients to do what I
think
> they should. Perhaps it's my failure to use a contrast matrix. Or
something else.
>
> Any suggestions? I'll be really grateful for any advice.
>
> Thanks!
>
> - Paul
